• 방송공학회논문지
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• 제10권3호
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• pp.357-371
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• 2005

본 논문에서는 CDS(Cross-Diamond Search algorithm) 및 CDHSs(Cross-Diamond-Hexagonal Search algorithms)의 성능을 향상시키기 위하여 탐색 영역의 위치에 따라 최적의 탐색 형태를 적용하는 CDTS(Cross-Diamond-Triangle Search algorithm)를 제안한다. CDTS에서 탐색 영역의 위치에 따라 최적의 탐색 형태를 적용하기 위하여 다양한 실험 영상들의 움직임 분포를 먼저 분석하였다. 분석된 움직임 분포에 근거하여 CDTS 구현 시 탐색 영역 중심부에서는 십자 탐색 형태와 다이아몬드 탐색 형태를 적용하고, 나머지 탐색 영역에서는 삼각 탐색 형태와 다이아몬드 탐색 형태를 적용한다. CDTS에서 제안하는 삼각 탐색 형태는 기존 탐색 알고리즘에서 사용하는 대칭형 구조와는 다르게 비대칭형 구조를 가지고 탐색점을 더욱 감소시키는 효과를 제공하면서도 화질을 유지할 수 있다. CDTS를 CDS 및 CDHSs와 비교하였을 때 화질 열화 없이 각각 평균 16.22$\%$ 및 3.09$\%$ 정도의 탐색점 감소 효과가 나타났다.

• 한국지능시스템학회논문지
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• 제8권3호
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• pp.71-79
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• 1998

본 논문은 유전알고리즘과 random tabu 탐색법을 조합한 새로운 최적화 알고리즘을 제안한다. 유전알고리즘과 전역적인 최적해에 대한 탐색능력이 우수하고, random tabu 탐색법은 최적해에의 수렴속도가 매우 빠른 알고리즘이다. 본 논문에서는 이 두 알고리즘의 장점을 이용해서 수렴정도와 수렴속도가 더욱 향상된 최적알고리즘을 제안하여 알고리즘의 수렴성능을 조사하고, 실제 최적화문제로서 지진응답을 최소로 하기위한 배관지지대의 최적배치문제에 적용하여 기존의 방법과 비교를 통하여 유용성을 검토하였다.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Structural Engineering and Mechanics
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• 제29권4호
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• pp.391-410
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• 2008

In this article, a harmony search algorithm is presented for optimum design of steel frame structures. Harmony search is a meta-heuristic search method which has been developed recently. It is based on the analogy between the performance process of natural music and searching for solutions of optimization problems. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraint for columns were imposed on frames. The results of harmony search algorithm were compared to those of the other optimization algorithms such as genetic algorithm, optimality criterion and simulated annealing for two planar and two space frame structures taken from the literature. The comparisons showed that the harmony search algorithm yielded lighter designs for the design examples presented.

• Steel and Composite Structures
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• 제9권6호
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• pp.535-555
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• 2009

The harmony search method based optimum design algorithm is presented for geometrically non-linear semi-rigid steel frames. Harmony search method is recently developed metaheuristic algorithm which simulates the process of producing a musical performance. The optimum design algorithm aims at obtaining minimum weight steel frames by selecting from standard set of steel sections such as European wide flange beams (HE sections). Strength constraints of Turkish Building Code for Steel Structures (TS648) specification and displacement constraints were used in the optimum design formulation. The optimum design algorithm takes into account both the geometric non-linearity of the frame members and the semi-rigid behaviour of the beam-to-column connections. The Frye-Morris polynomial model is used to calculate the moment-rotation relation of beam-to-column connections. The robustness of harmony search algorithm, in comparison with genetic algorithms, is verified with two benchmark examples. The comparisons revealed that the harmony search algorithm yielded not only minimum weight steel frames but also required less computational effort for the presented examples.

• ETRI Journal
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• 제39권6호
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• pp.782-793
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• 2017

This paper considers the use of the Partial Transmit Sequence (PTS) technique to reduce the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing signal in wireless communication systems. Search complexity is very high in the traditional PTS scheme because it involves an extensive random search over all combinations of allowed phase vectors, and it increases exponentially with the number of phase vectors. In this paper, a suboptimal metaheuristic algorithm for phase optimization based on an improved harmony search (IHS) is applied to explore the optimal combination of phase vectors that provides improved performance compared with existing evolutionary algorithms such as the harmony search algorithm and firefly algorithm. IHS enhances the accuracy and convergence rate of the conventional algorithms with very few parameters to adjust. Simulation results show that an improved harmony search-based PTS algorithm can achieve a significant reduction in PAPR using a simple network structure compared with conventional algorithms.

• 한국컴퓨터산업학회논문지
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• 제4권12호
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• pp.953-964
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• 2003

서로 다른 형태와 크기를 가지는 탐색패턴과 움직임 벡터의 분포는 블록 정합 알고리즘에서 탐색 속도와 화질을 좌우하는 중요한 요소이다. 본 논문에서는 크로스패턴과 납작한 육각패턴을 이용한 새로운 고속 블록 정합 알고리즘을 제안한다. 이 알고리즘은 초기에 크로스 패턴을 이용하여 탐색영역의 중심 주위에 분포 확률이 높은 움직임이 작은 벡터를 우선 찾은 다음에 움직임이 큰 벡터에 대해서는 납작한 육각패턴을 이용하여 고속으로 움직임 벡터를 찾게 하였다. 실험결과, 제안된 알고리즘은 육각패턴 탐색 알고리즘에 비하여 움직임 벡터 추정의 속도에 있어서 약 0.2-6.2% 의 성능 향상을 보였으며 화질 또한 PSNR 기준으로 약 0.02-0.3105 의 향상을 보였다.

• 한국인터넷방송통신학회논문지
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• 제17권5호
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• pp.157-163
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• 2017

데이터 탐색법 중 가장 널리 알려진 이진법은 평균과 최악의 경우 $O(log_2n)$, 보간법은 평균 $O(log_2log_2n)$, 최악의 경우 O(n)의 수행 복잡도를 갖고 있다. 또한 기존의 보간탐색법은 사전정보없이 킷값이 확률적으로 위치한 정보에 근거하여 탐색을 한다. 본 논문에서는 데이터의 MSB 인덱스를 블록으로 하는 블록탐색법으로 해당 블록범위를 결정하고, 블록 내에서는 보간법을 적용하여 탐색하는 하이브리드 블록과 보간탐색 알고리즘을 제안한다. 제안된 알고리즘은 블록탐색법의 사전 정보를 활용하여 탐색범위를 축소시키고 축소된 탐색범위내에서 무정보 방법으로 탐색하는 방법으로 평균과 최악의 경우 모두 수행복잡도는 $O(log_2log_2n_i)$, $n_i{\simeq}0.1n$으로 보간탐색법의 평균 수행복잡도에 비해 10배 정도 시간을 단축시킬 수 있다.

• 통합자연과학논문집
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• 제2권2호
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• pp.55-58
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• 2009

A ligand-receptor docking program is an indispensible tool in modern pharmaceutical design. An accurate prediction of small molecular docking pose to a receptor is essential in drug design as well as molecular recognition. An effective docking program requires the ability to locate a correct binding pose in a surprisingly complex conformational space. However, there is an inherent difficulty to predict correct binding pose. The odds are more demanding than finding a needle in a haystack. This mainly comes from the flexibility of both ligand and receptor. Because the searching space to consider is so vast, receptor rigidity has been often applied in docking programs. Even nowadays the receptor may not be considered to be fully flexible although there have been some progress in search algorithm. Improving the efficiency of searching algorithm is still in great demand to explore other applications areas with inherently flexible ligand and/or receptor. In addition to classical search algorithms such as molecular dynamics, Monte Carlo, genetic algorithm and simulated annealing, rather recent algorithms such as tabu search, stochastic tunneling, particle swarm optimizations were also found to be effective. A good search algorithm would require a good balance between exploration and exploitation. It would be a good strategy to combine algorithms already developed. This composite algorithms can be more effective than an individual search algorithms.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.433-439
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• 2019

Artificial bee colony algorithm is a strong global search algorithm which exhibits excellent exploration ability. The conventional ABC algorithm adopts employed bees, onlooker bees and scouts to cooperate with each other. However, its one dimension and greedy search strategy causes slow convergence speed. To enhance its performance, in this paper, we abandon the greedy selection method and propose an artificial bee colony algorithm with special division and intellective search (ABCIS). For the purpose of higher food source research efficiency, different search strategies are adopted with different employed bees and onlooker bees. Experimental results on a series of benchmarks algorithms demonstrate its effectiveness.